{"id":17526,"date":"2026-06-24T16:31:39","date_gmt":"2026-06-24T16:31:39","guid":{"rendered":"https:\/\/siliconvalleymovingpost.com\/?p=17526"},"modified":"2026-06-24T16:31:39","modified_gmt":"2026-06-24T16:31:39","slug":"all-the-worlds-a-robot-staging-ground-for-tech-entrepreneurs-building-physical-ai","status":"publish","type":"post","link":"https:\/\/siliconvalleymovingpost.com\/?p=17526","title":{"rendered":"All the world\u2019s a robot-staging ground for tech entrepreneurs building \u2018physical AI\u2019"},"content":{"rendered":"
\n

By MATT O\u2019BRIEN, AP Technology Writer<\/strong><\/p>\n

PROVIDENCE, R.I. (AP) \u2014 Computer scientist Louis Castricato was in his eighth year studying large language models \u2014 the artificial intelligence technology behind chatbots like ChatGPT and Claude \u2014 when he started to feel like he was hitting a dead end.<\/p>\n

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\u201cWe basically have passed the point of doing real fundamental LLM research,\u201d Castricato said. \u201cNow it\u2019s just applications.\u201d<\/p>\n

The researcher quit his studies at Brown University and started a new company, called Overworld. Its ambition is in its name: AI that can understand and navigate a world, not just words.<\/p>\n

There\u2019s still plenty of money to be made from AI chatbots \u2014 investors are counting on it as they commit trillions of dollars to leading developers like Anthropic and OpenAI. But a growing number of AI entrepreneurs are dedicating themselves to what they see as the next frontier: \u201cworld models\u201d that teach AI systems, and sometimes robots, how to react in a physical environment.<\/p>\n

They include some of the field\u2019s most prominent scientists, such as \u201cGodmother of AI\u201d Fei-Fei Li, who describes the concept of a world model as \u201cone of the most important and most overloaded terms in AI today.\u201d<\/p>\n

Scientists are applying AI in new dimensions with \u2018world models\u2019<\/h4>\n

At the heart of world model research is the idea that AI can\u2019t be truly intelligent if it can only read a book. It also needs to read the room.<\/p>\n

\u201cWhere language models learn the statistical structure of text, world models learn the statistical structure of space and time: how light falls on a surface, how a garden looks from an angle no camera has captured, how objects respond to force and follow the laws of physics,\u201d wrote Li, founder of the San Francisco startup World Labs, in an essay published this month.<\/p>\n

\n<\/div>\n

Another proponent is AI pioneer Yann LeCun, who quit his job as Meta\u2019s chief AI scientist last year to start Paris-based Advanced Machine Intelligence Labs.<\/p>\n

\u201cWorld model is quickly becoming a buzzword,\u201d LeCun said on a recent \u201cUnsupervised Learning\u201d podcast. He said he views it as something that enables an AI agent \u201cto predict the consequences of its own actions.\u201d<\/p>\n

There are multiple ways of defining world models, often based on the technologies someone hopes to build with it \u2014 be it robots or a more interactive video game.<\/p>\n

Robots can\u2019t learn much from AI models trained on books<\/h4>\n

Training on all of humanity\u2019s books, news articles and visual media, as AI language models have done, has led to AI assistants that are changing the nature of office-based work and some creative fields. But some proponents see limitations in generative AI models that work by repeatedly predicting the next word or pixel to produce new dialogue, images or lines of code.<\/p>\n

\n<\/div>\n

Chatbots can\u2019t pick up a coffee mug, notes Martial Hebert, dean of computer science at Carnegie Mellon University.<\/p>\n

\u201cThere\u2019s all the geometry of the world, the dynamic of how I move my hand, the physical interaction of the contact with the cup,\u201d Hebert said. \u201cThis is much more complex than just predicting the next word in a sentence.\u201d<\/p>\n

For scientists like Hebert, who has spent more than four decades researching robotics, the most useful application for world models is as a faster and cheaper path to \u201cphysical AI\u201d \u2014 another tech industry buzzword.<\/p>\n

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\u201cSome people may have different definitions, but physical and embodied AI are kind of the evolution of what we used to call robotics,\u201d Hebert said in an interview. Some of the AI advances that have made chatbots so useful can also be applied to building AI with a broad enough awareness of its environment to work like a robot\u2019s brain, he said.<\/p>\n

\u201cIn your body and spinal cord you have a very general model of how to balance, how to walk around, and you can adapt to your knee hurting in the morning, so you now walk a little differently,\u201d he said. \u201cYou don\u2019t need to think about that. You have a general model somewhere in your nervous system and brain that allows your body to adapt very quickly.\u201d<\/p>\n

Simulated worlds are drawing interest from investors<\/h4>\n

Smarter robots aren\u2019t the only end game for world models. Castricato started Overworld last year and the tiny Rhode Island-based startup is now building video game worlds where a scene, say, of a spooky forest, can adapt as a virtual character moves through it and interacts with the objects in it.<\/p>\n

\u201cThere\u2019s no other world model where you can just walk through doors or where you can interact with a detailed environment like this,\u201d he said in an interview. \u201cWe optimize for interaction above anything else.\u201d<\/p>\n

While the near-term applications aren\u2019t as readily apparent as AI coding tools, world model makers are attracting interest from venture capitalists like Steve Jang, co-founder and managing partner at Kindred Ventures.<\/p>\n

The firm is investing in Overworld and other world model-focused companies, including Causal Labs, which is building AI models for weather prediction, and Extropic, which is building specialized computer chips suited to world models.<\/p>\n

\u201cI think that the future is many different types of models with many different philosophies and architectures,\u201d Jang said. \u201cI don\u2019t think that it\u2019ll be one large, dense model to rule them all.\u201d<\/p>\n

In her recent essay, Li sought to create a \u201ctaxonomy of world models\u201d to help sort out the confusion about the competing visions.<\/p>\n

\u201cA video model that produces gorgeous but physically impossible flames, a language model improvising a playable game, and a physics engine that faithfully simulates combustion all go by the same name,\u201d she wrote.<\/p>\n

She divided world models into three categories. The most commercially viable today are \u201crenderers\u201d that prioritize the visual fidelity of the virtual worlds they create but can\u2019t be trusted to teach robots much.<\/p>\n

Then, there are \u201csimulators\u201d that create virtual training grounds that faithfully represent the physical structure of a world; and \u201cplanners\u201d that try to predict what an AI agent or robot should do in an unstructured world.<\/p>\n

\u201cA robot that can plan is a robot that can work, and the entire industry is racing to be the one that gets there first,\u201d she wrote.<\/p>\n

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Experts are shifting focus to world models that teach AI systems how to understand space, time and physical environments.<\/p>\n","protected":false},"author":1,"featured_media":17525,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[43,2],"tags":[],"class_list":["post-17526","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-based-on-facts-either-observed-and-verified-directly-by-the-reporter-or-reported-and-verified-from-knowledgeable-sources","category-news"],"yoast_head":"\nAll the world\u2019s a robot-staging ground for tech entrepreneurs building \u2018physical AI\u2019 - Silicon Valley Moving Post<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/siliconvalleymovingpost.com\/?p=17526\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"All the world\u2019s a robot-staging ground for tech entrepreneurs building \u2018physical AI\u2019 - 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